import datetime import os import torch import matplotlib matplotlib.use('Agg') import scipy.signal from matplotlib import pyplot as plt from torch.utils.tensorboard import SummaryWriter class LossHistory(): def __init__(self, log_dir, model, input_shape): time_str = datetime.datetime.strftime(datetime.datetime.now(),'%Y_%m_%d_%H_%M_%S') self.log_dir = os.path.join(log_dir, "loss_" + str(time_str)) self.losses = [] self.val_loss = [] os.makedirs(self.log_dir) self.writer = SummaryWriter(self.log_dir) try: dummy_input = torch.randn(2, 3, input_shape[0], input_shape[1]) self.writer.add_graph(model, dummy_input) except: pass def append_loss(self, epoch, loss, val_loss): if not os.path.exists(self.log_dir): os.makedirs(self.log_dir) self.losses.append(loss) self.val_loss.append(val_loss) with open(os.path.join(self.log_dir, "epoch_loss.txt"), 'a') as f: f.write(str(loss)) f.write("\n") with open(os.path.join(self.log_dir, "epoch_val_loss.txt"), 'a') as f: f.write(str(val_loss)) f.write("\n") self.writer.add_scalar('loss', loss, epoch) self.writer.add_scalar('val_loss', val_loss, epoch) self.loss_plot() def loss_plot(self): iters = range(len(self.losses)) plt.figure() plt.plot(iters, self.losses, 'red', linewidth = 2, label='train loss') plt.plot(iters, self.val_loss, 'coral', linewidth = 2, label='val loss') try: if len(self.losses) < 25: num = 5 else: num = 15 plt.plot(iters, scipy.signal.savgol_filter(self.losses, num, 3), 'green', linestyle = '--', linewidth = 2, label='smooth train loss') plt.plot(iters, scipy.signal.savgol_filter(self.val_loss, num, 3), '#8B4513', linestyle = '--', linewidth = 2, label='smooth val loss') except: pass plt.grid(True) plt.xlabel('Epoch') plt.ylabel('Loss') plt.legend(loc="upper right") plt.savefig(os.path.join(self.log_dir, "epoch_loss.png")) plt.cla() plt.close("all")